Numpy arange to create array by using start stop and step

numpy.arange(start,stop, step,dtype=None)

Return ndarray by using start, stop, step and dtype.

`start`	number, Optional,default is 0, Start value of the elements
`stop`	number, Optional,Upper limit of start ( value not included ).
`step`	number, Optional, default is 1
`dtype`	type of output, Optional, default is dtype of input arguments

Examples

Creating array ( start = 0 )

import numpy as np
print(np.arange(0)) # []

print(np.arange(5)) # [0 1 2 3 4]

With start stop and step options

print(np.arange(start=1,stop=5,step=2)) # [1 3]

print(np.arange(1,5))

Output

[1 2 3 4]

Creating empty array

x=np.arange(3,3)
print(x) # []

Sample codes below are with output.

print(np.arange(start=1,stop=5,step=2)) # [1 3]

print(np.arange(1,5,2)) # [1 3]

print(np.arange(-10,-3,2)) # [-10  -8  -6  -4]

print(np.arange(-3,-10,-2)) # [-3 -5 -7 -9]

print(np.arange(-3,10,3)) # [-3  0  3  6  9]

print(np.arange(.4, 2.8,.7)) # [0.4 1.1 1.8 2.5]

print(np.arange(-2.8, 2,.9)) # [-2.8 -1.9 -1.  -0.1  0.8  1.7]

We can use option dtype ( dtype=np.int32 )

print(np.arange(1,5,dtype=np.int8)) # [1 2 3 4]

print(np.arange(1,5,dtype=np.float64)) # [1. 2. 3. 4.]

Getting the dtype

my_ar=np.arange(1,5,dtype=np.float64)
print(my_ar.dtype) # float64